Book recommendation for masters student with no maths background

I recommend checking out the recent book An Introduction to Stochastic Differential Equations by Evans, who is the author of a very popular PDEs textbook. An Introduction to Stochastic Differential Equations is a short, intuitive, friendly book. Here's the amazon description:

This short book provides a quick, but very readable introduction to stochastic differential equations, that is, to differential equations subject to additive "white noise" and related random disturbances. The exposition is concise and strongly focused upon the interplay between probabilistic intuition and mathematical rigor. Topics include a quick survey of measure theoretic probability theory, followed by an introduction to Brownian motion and the Itô stochastic calculus, and finally the theory of stochastic differential equations. The text also includes applications to partial differential equations, optimal stopping problems and options pricing. This book can be used as a text for senior undergraduates or beginning graduate students in mathematics, applied mathematics, physics, financial mathematics, etc., who want to learn the basics of stochastic differential equations. The reader is assumed to be fairly familiar with measure theoretic mathematical analysis, but is not assumed to have any particular knowledge of probability theory (which is rapidly developed in Chapter 2 of the book).

For linear algebra, I recommend Gilbert Strang's book Linear Algebra and its Applications, which makes the subject seem easy and provides good intuition.

I recommend An Elementary Introduction to Mathematical Finance by Sheldon M. Ross.

From the Amazon review:

This textbook on the basics of option pricing is accessible to readers with limited mathematical training. It is for both professional traders and undergraduates studying the basics of finance. Assuming no prior knowledge of probability, Sheldon M. Ross offers clear, simple explanations of arbitrage, the Black-Scholes option pricing formula, and other topics such as utility functions, optimal portfolio selections, and the capital assets pricing model. Among the many new features of this third edition are new chapters on Brownian motion and geometric Brownian motion, stochastic order relations, and stochastic dynamic programming, along with expanded sets of exercises and references for all the chapters.

For partial differential equations, I recommend The mathematics of financial derivatives: a student introduction by P. Wilmott, S. Howison, and J. Dewynne.

This book avoids almost all discussion of diffusion processes associated with option pricing, focusing instead as much as possible on the associated PDE’s. Relatively easy to read; it goes much further on numerical approximation schemes, American options, and some other PDE-related topics.

For linear algebra, I can suggest Schaum's Outline of Linear Algebra.

Hi I am currently a Mathematics Masters student having come in from a course with only moderate mathematical content. I use Walter Rudin's 'Principles of Mathematical Analysis' as my first stop to check anything related to analysis .i.e. Fourier Transform. It may not be the best choice of book for linear algebra etc but I thought I would share and recommend having a look!